Papers
Pre-training Context and Time Aware Location Embeddings from Spatial-Temporal Trajectories for User Next Location Prediction
Yan Lin, Huaiyu Wan, Shengnan Guo et al.
Preventing Overfitting via Sample Reweighting for Recommender System Incremental Update (Student Abstract)
Danni Peng, Xiaobo Hu, Anxiang Zeng et al.
Proactive Privacy-preserving Learning for Retrieval
Peng-Fei Zhang, Zi Huang, Xin-Shun Xu
Probabilistic Dependency Graphs
Oliver Richardson, Joseph Y Halpern
Probabilistic Programming Bots in Intuitive Physics Game Play
Fahad Alhasoun, Sarah Alneghiemish
Probing Product Description Generation via Posterior Distillation
Haolan Zhan, Hainan Zhang, Hongshen Chen et al.
Programmatic Strategies for Real-Time Strategy Games
Julian R. H. Mariño, Rubens O. Moraes, Tassiana C. Oliveira et al.
Progression Heuristics for Planning with Probabilistic LTL Constraints
Ian Mallett, Sylvie Thiebaux, Felipe Trevizan
Progressive Multi-task Learning with Controlled Information Flow for Joint Entity and Relation Extraction
Kai Sun, Richong Zhang, Samuel Mensah et al.
Progressive Network Grafting for Few-Shot Knowledge Distillation
Chengchao Shen, Xinchao Wang, Youtan Yin et al.
Progressive One-shot Human Parsing
Haoyu He, Jing Zhang, Bhavani Thuraisingham et al.
Projection-Free Bandit Optimization with Privacy Guarantees
Alina Ene, Huy L. Nguyen, Adrian Vladu
Projection-free Online Learning in Dynamic Environments
Yuanyu Wan, Bo Xue, Lijun Zhang
Projection-free Online Learning over Strongly Convex Sets
Yuanyu Wan, Lijun Zhang
Project RISE: Recognizing Industrial Smoke Emissions
Yen-Chia Hsu, Ting-Hao (Kenneth) Huang, Ting-Yao Hu et al.
Proof of Learning (PoLe): Empowering Machine Learning with Consensus Building on Blockchains (Demo)
Yixiao Lan, Yuan Liu, Boyang Li et al.
Proportionally Representative Participatory Budgeting with Ordinal Preferences
Haris Aziz, Barton E. Lee
Proportional Representation under Single-Crossing Preferences Revisited
Andrei Costin Constantinescu, Edith Elkind
Proposal-Free Video Grounding with Contextual Pyramid Network
Kun Li, Dan Guo, Meng Wang
Protecting the Protected Group: Circumventing Harmful Fairness
Omer Ben-Porat, Fedor Sandomirskiy, Moshe Tennenholtz
Provable Benefits of Overparameterization in Model Compression: From Double Descent to Pruning Neural Networks
Xiangyu Chang, Yingcong Li, Samet Oymak et al.
Provably Good Solutions to the Knapsack Problem via Neural Networks of Bounded Size
Christoph Hertrich, Martin Skutella
Provably Secure Federated Learning against Malicious Clients
Xiaoyu Cao, Jinyuan Jia, Neil Zhenqiang Gong